Data Science Weekend - Datathon Challenge

Team Name: Industr-igate

Members:

Project Summary and Goal:

The COVID-19 Pandemic is one of the most unprecendented events in human history and for most of us, the most monumental global event we have come to witness. It has impacted every aspect of daily life from mental health to socialization tactics to the theft and prices of puppies skyrocketing in the past one year. There are several ways to investigate the effect of COVID-19 on human behaviour, and the one way we have chosen to do that is to look at how this era has impacted differnt industries. Through stock data, we cna see the human response to the pandemic as people put their money where they think there is value. Some companies sunk, some swam and some built a Noah's ark and cruised. This analysis is highlighting which copmanies, and ultimately, which industries did just that.

Research Question:

What companies or industries have benefited from the pandemic? What new businesses have been created in response to the pandemic?

Method / Approach:

The approach taken to investigate this research was to obtain stock price data for over 4,000 companies from the Robinhood trading app from Ocotber 2019 to present day. The mean price of each stock for October 2019 was compared to the mean price of October 2020. This is because October 2019 was shortly before the pandemic which showcases the company's/industry's publicly perceived value before widespread panic about the pandemic broke while by October 2020, the initial frenzy surrouding the pandemic had meted out and allowed for the public perceived value of the cmopany to be reflective of what they truly thought of the company's value in a pandemic crisis.

Robinhood was chosen due to it's vast user base of over 15 million people and wide array of stocks as users have access to over 5,000 stocks. This was taken into consideration to eliminate selection bias as the Robinhood userbase is fairly representative of the vast majority of America's public due to the fact that it requires very little capital to begin investing.

About the data:

The data was obtained using python code from this website: https://robin-stocks.readthedocs.io/en/latest/ to access the stock price data through the Robinhood API. For ech stock in Robinhood, the data detalis the industry of the stock, stock ticker, stock name and stock price - these were the relevant data fields that were used to conduct the analysis.

Exploratory Data Analysis:

Firstly, in order to investigate what industries have prospered during the COVID-19 pandemic, we will take a look at UK goverment supplied data about births as well as deaths of new businesses in the time frame form 2017 to 2020.

ONS data source

Note: Data is going to by scaled (divided by standard deviation) in order to get better insights.
Note: One can play with variables visible on the graph, by simply clicking or unclicking them from the legend.

Births per Industry

COMMENTS

The biggest increase in businesses births, in comparison to pre and after Q2 2020 (time when lockdown laws after first wave started to ease) is visible in following industries:

While biggest decrease in businesses births can be visible in following industries:

Deaths per Industry

COMMENTS

The biggest increase in businesses births, in comparison to pre and after Q2 2020 (time when lockdown laws after first wave started to ease) is visible in following industries:

While biggest decrease in businesses births can be visible in following industries:

Stock Price Analysis

Top 50 companies growth by industry

Bottom 50 Companies Growth by Stock Prices by Sector

Sector Analysis

Here we analyse the growth we obtained before over different sectors.

Industry Analysis

Top 100 companies with market share increases (from FT)

To aquire data for top 100 companies, we will webscrape the data from a Financial Times article. Financial Times doesn't allow for webscraping using requests tool in python, however one of us had subsription and was able to download the source code to the text file, that was used to extract required data.

The aquired data can summarised in a tabular form as below.

COMMENT:

Top companies are Tesla, Sea Group and Zoom Video. We will now aggregate data per industry.

COMMENT:

It's visible that the sectors with biggest increase are Home, Video and Automotive. At the smae time, sectors with biggest end-2020 market value are Ecommerce, Online and Automotive.

Conclusion

Insights:

From the graphs above, we see that the top 5 industries to thrive during the pandemic were:

while the top 5 to sink were:

As this data is specific to companies' stock data, there are clashes withing industries such as the Technology services industries as the rise or fall of a major company in that industry could influence the overall performance of that industry.

Project Limitations and Possible Improvements:

As with any piece of work, there are always improvements that can be made. Below are the top limitations and imporvements that could be made to improve the accuracy of this analysis:

Limitations:

Improvements: